AxonAI runs autonomous agents around the clock — detecting anomalies, correlating signals across thousands of devices, and triggering self-healing workflows before failures reach engineers.
The problem
of infrastructure outages are caused by undetected degradation that human shifts miss.
average cost per hour of unplanned downtime in enterprise IoT environments.
average time to detect a cascading failure after the first symptom appears.
ops teams burning out trying to maintain continuous coverage across global infrastructure.
Capabilities
Every layer of AxonAI is designed to operate continuously — ingesting millions of data points per second, making decisions at the edge, and keeping systems running without human intervention.
Edge AI agents analyze telemetry in real time — no cloud round-trip required. Anomaly signals are correlated across device clusters before alerts fire.
When a fault is detected, AxonAI executes pre-approved remediation playbooks automatically — restarting services, rerouting traffic, isolating failing nodes.
ML models trained on your infrastructure fingerprint predict degradation hours before it becomes a failure — giving engineers time to act.
Every agent runs with least-privilege access. All telemetry is signed and encrypted in transit and at rest. SOC 2 Type II certified.
Local agents make millisecond decisions; the cloud model aggregates cross-fleet signals for systemic pattern detection that edge alone cannot see.
From signal spike to engineer alert — including classification, deduplication, and routing — in under 200 milliseconds at the 99th percentile.
Process
Four stages, fully automated. Each decision is logged, explainable, and reversible — giving engineering teams visibility and control without requiring them to be on-call 24/7.
AxonAI connects to your IoT device fleet via secure MQTT or REST endpoints at the edge. Telemetry streams — metrics, logs, events, traces — are normalized and signed in real time.
Supports OPC-UA, MQTT, REST, and industrial SCADA protocols.
Edge ML models evaluate every signal against learned baselines. Anomalies are classified by severity and correlated across device groups before any alert is issued.
Runs on device-class hardware with 512MB RAM and 1GHz ARM cortex.
Validated anomalies trigger pre-approved remediation playbooks — service restarts, traffic rerouting, firmware rollback — without waiting for a human in the loop.
Playbooks are configurable; all actions are logged for audit.
Engineers receive structured alerts with context, root hypothesis, and recommended action — via Slack, PagerDuty, email, or webhook — only when human judgment is needed.
Alert fatigue reduction: >90% of alerts auto-resolved.
Market momentum
AxonAI is positioned at the intersection of two explosive growth curves: AI-driven predictive maintenance (30.3% CAGR) and autonomous IoT infrastructure management.
Traffic, water, power grid monitoring
Manufacturing, robotics, PLCs
Fleet health, uptime, safety systems
Data centers, network, storage
Get started
AxonAI deploys in under an hour. Connect your first device cluster, define your remediation playbooks, and let autonomous agents take over — with full audit logs and rollback capability.
Reach us directly at axonai-3@polsia.app